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  • 1.
    Buckland, Philip I.
    et al.
    Umeå University, Faculty of Arts, Department of historical, philosophical and religious studies, Environmental Archaeology Lab.
    Nyqvist, Roger
    Umeå University, Faculty of Arts, Department of historical, philosophical and religious studies, Environmental Archaeology Lab.
    Alexander, Benedict
    WSP, Sweden.
    Palsson, Gisli
    Umeå University, Faculty of Arts, Department of historical, philosophical and religious studies, Environmental Archaeology Lab.
    Eriksson, Samuel
    Umeå University, Faculty of Arts, Department of historical, philosophical and religious studies, Environmental Archaeology Lab.
    The Swedish Transport Administration’s Toolbox and its Potential in Archaeological and Cultural Heritage Survey: Including a brief review of remote sensing, prospection and geodata analysis methods for archaeology and cultural heritage2018Report (Other academic)
    Abstract [en]

    This report provides an overview of the main remote sensing methods and geodata types used in archaeological prospection and cultural heritage survey. Based on a literature review, it provides an initial survey of the state of the art nationally and internationally, followed by details on the potential usage of different methods in a Swedish context. The details include pros and cons of methods as well as information on considerations that should be taken into account when applying the methods in different situations. Examples are provided where relevant to explain specific details or illustrate important points. Particular attention has been paid to laser scanning (LiDAR) data due to its increasing prevalence and prominence in landscape and archaeological surveys.

    The report continues with a preliminary evaluation of the possibilities for using data provided by Swedish Transport Administration (Trafikverket), obtained for other stages of the planning process, in archaeological and cultural heritage work. Specifically, the report looks at a number of geodata types obtained from The Geological Survey of Sweden (Sveriges geologiska undersökning/SGU), a nature conservation survey in report form, a ground penetrating radar technical report, terrain laser scanning (LiDAR) and orthophotos (geometrically corrected aerial photographs). The SGU geodata consist of a number of Geographical Information System (GIS) layers describing bedrock and soil types, and the nature conservation survey included accompanying, but incomplete, GIS data. This section consists of concise descriptions of the potential of each group of GIS layers or data, and is complemented by brief, bullet point summaries along with additional technical information in Appendix 1. Comments have been made where additional, related, data sources would be useful. Swedish terms are included in parenthesis where the term differs significantly from the English equivalent.

    A final summary provides a compact overview of the main points of the report before providing some conclusions and ideas for further work. This is in turn followed by a list of ideas for enhancing the efficiency with which the types of data discussed can be used in infrastructure projects which have a potential to impact on archaeology/cultural heritage.

    References are provided to support important or potentially contentious points or where further reading or research would be advised for a more comprehensive understanding of relevant issues.

  • 2.
    Cheng, Xiaogang
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China; School of Electrical Engineering and Computer Science, Royal Institute of Technology, Stockholm, Sweden.
    Yang, Bin
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. School of Environmental and Municipal Engineering, Xi’an University of Architecture and Technology, Xi'an, China.
    Liu, Guoqing
    Olofsson, Thomas
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Li, Haibo
    A total bounded variation approach to low visibility estimation on expressways2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 2, article id 392Article in journal (Refereed)
    Abstract [en]

    Low visibility on expressways caused by heavy fog and haze is a main reason for traffic accidents. Real-time estimation of atmospheric visibility is an effective way to reduce traffic accident rates. With the development of computer technology, estimating atmospheric visibility via computer vision becomes a research focus. However, the estimation accuracy should be enhanced since fog and haze are complex and time-varying. In this paper, a total bounded variation (TBV) approach to estimate low visibility (less than 300 m) is introduced. Surveillance images of fog and haze are processed as blurred images (pseudo-blurred images), while the surveillance images at selected road points on sunny days are handled as clear images, when considering fog and haze as noise superimposed on the clear images. By combining image spectrum and TBV, the features of foggy and hazy images can be extracted. The extraction results are compared with features of images on sunny days. Firstly, the low visibility surveillance images can be filtered out according to spectrum features of foggy and hazy images. For foggy and hazy images with visibility less than 300 m, the high-frequency coefficient ratio of Fourier (discrete cosine) transform is less than 20%, while the low-frequency coefficient ratio is between 100% and 120%. Secondly, the relationship between TBV and real visibility is established based on machine learning and piecewise stationary time series analysis. The established piecewise function can be used for visibility estimation. Finally, the visibility estimation approach proposed is validated based on real surveillance video data. The validation results are compared with the results of image contrast model. Besides, the big video data are collected from the Tongqi expressway, Jiangsu, China. A total of 1,782,000 frames were used and the relative errors of the approach proposed are less than 10%.

  • 3.
    Garrison, Thomas G.
    et al.
    Umeå University, Faculty of Arts, Humlab.
    Chapman, Bruce
    Houston, Stephen
    Roman, Edwin
    Garrido Lopez, Jose Luis
    Discovering ancient Maya settlements using airborne radar elevation data2011In: Journal of Archaeological Science, ISSN 0305-4403, E-ISSN 1095-9238, Vol. 38, no 7, p. 1655-1662Article in journal (Refereed)
    Abstract [en]

    This report presents the results of using NASA/JPL airborne synthetic aperture radar data (AIRSAR) to detect ancient Maya settlements beneath jungle canopy in Guatemala. AIRSAR stands out from previous applications of radar remote sensing in the Maya lowlands because of its canopy-penetrating capabilities. The authors offer an overview of the AIRSAR technology, followed by a case study in which the AIRSAR data receive testing in the field. Reconnaissance in the region around the Maya site of El Zotz led to the discovery of two new sites, including the medium-sized settlement of La Avispa. AIRSAR also aided archaeologists in detecting zones of residential settlement around the site core of El Zotz. This research will serve as a guide for future applications of radar remote sensing in Maya archaeology. (C) 2011 Elsevier Ltd. All rights reserved.

  • 4.
    Haake, Johan
    et al.
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Björk, Peter
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Karlsson, Johannes
    Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Demonstration abstract: positioning by synchronized IR light2014In: Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (IPSN' 14), IEEE conference proceedings, 2014, p. 335-336Conference paper (Refereed)
    Abstract [en]

    In this paper we will describe a positioning system based on synchronized IR light. Each node will be assigned a timeslot where they will send out an IR light. There is an IR camera that is also synchronized to the timeslots that will detect the position of each node and the ID that corresponds to the timeslot. To synchronize the clock of all nodes an IR flashlight is sent out that is detected by a photodiode on the nodes. The demo will show live video stream from a network camera where the ID and position of each node in view will be overlaid in real-time in the video.

  • 5.
    Mattias, Tjernqvist
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Backpack-based inertial navigation and LiDAR mapping in forest environments2017Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Creating 3D models of our surrounding world has seen a rapid increase in research and development over the last few years. A common method is to use laser scanners. Mapping is done either by ground based systems or airborne systems. With stationary ground-based laser scanning, or terrestrial laser scanning (TLS), it is possible to obtain high accuracy point clouds. But stationary TLS can often be a cumbersome and time-demanding task due to its lack of mobility. Because of this, much research has gone into mobilised TLS systems, referred commonly to as mobile laser scanning (MLS). Georeferencing point clouds to a world coordinate system is a difficult task in environments where global navigation satellite systems (GNSS) is unreliable. One such environment is forests, where the GNSS signal can be blocked, absorbed or reflected from the trees and canopy. Accurate georeference of points clouds for MLS systems in forests is difficult task that can be solved by using additional measurement instruments and post-processing algorithms to reduce the accumulation of errors, also known as drift. In this thesis a backpack-based MLS system to be used in forests was tested. The MLS system was composed of a GNSS, an inertial navigation unit (INS) and a laser scanner. The collected data was post-processed and analyzed to reduce the effects of detecting multiple ground layers and multiples of the same tree due to drift. The post-processing algorithm calculated tree and ground features to be used for adjusting the point cloud in the horizontal and vertical planes. The forest survey was done for an area roughly 40 meters in diameter. The MLS data was compared against TLS data as well as manual caliper data - where the caliper data was only measured in an area roughly 24 meters in diameter. The results indicated that the effects of multiple ground layers and multiple tree copies were removed after post-processing. Out of the total 214 TLS trees, 185 managed to be co-registered to MLS trees. The root mean square error (RMSE) and bias of the diameter at breast height (DBH) between the MLS andTLS data were 27.00 mm and -9.33 mm respectively. Co-registrationof the MLS and manual caliper data set gave 36 successful matches out of the total 43 manually measured DBH. The DBH RMSE and bias were 16.95 mm and -10.58 mm respectively. A Swedish TLS forest study obtained a DBH RMSE and bias (between TLS and caliper) of approximately 10 mm and +0.06 mm respectively. A Finnish backpack MLS forest study obtained a DBH RMSE and bias (between MLS and TLS) of 50.6 mm and +11.1 mm respectively. Evaluating the difference in radius at different heights along the tree stems between the MLS and TLS revealed a slight dependence on height, as the radius difference increased slightly closer to the stem base. The results indicated that backpack-based MLS systems has the potential for accurate lidar mapping in forests, and future development is of great interest to improve this system further.

  • 6. Olsson, Håkan
    et al.
    Skånes, Helle
    Tulldahl, Michael
    Wikström, Sofia
    Kautsky, Hans
    Rydell, Bengt
    Årnfelt, Erik
    Eklöf, Jan
    Steinvall, Ove
    Flygburen laser och digitala bilder för kartering och övervakning av akvatisk och terrester miljö2014Report (Other academic)
  • 7.
    Yu, Jun
    et al.
    Biostokastikum, SLU.
    Ranneby, Bo
    Biostokastikum, SLU.
    Nonparametric and probabilistic classification of agricultural crops using multitemporal images2006Conference paper (Refereed)
1 - 7 of 7
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